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This tutorial assumes that the reader already knows the basics of the Python programming
language. If you do not, the official Python
tutorial is excellent.

This tutorial assumes a decent mathematical background. Most examples require
knowledge up to calculus level, and some require knowledge at a calculus
level. Some of the advanced features require more than this. If you come
across a section that uses some mathematical function you are not familiar
with, you can probably skip over it, or replace it with a similar one that you
are more familiar with. Or look up the function on Wikipedia and learn
something new. Some important mathematical concepts that are not common
knowledge will be introduced as necessary.

The SymPy Live shell in the bottom corner will pop up and evaluate the code
block. You can also click any individual line to evaluate it one at a time.

The SymPy Live shell is a fully interactive Python shell. You can type any
expression in the input box to evaluate it. Feel free to use it throughout
the tutorial to experiment.

To show or hide the SymPy Live shell at any time, just click the green button
on the bottom right of the screen.

By default, the SymPy Live shell uses \(\LaTeX\) for output. If you want the
output to look more like the output in the documentation, change the
output format to Str or Unicode.

If you wish to modify an example before evaluating it, change the evaluation
mode to “copy” in the SymPy Live settings. This will cause clicking on an
example to copy the example to the SymPy Live shell, but not evaluate it,
allowing you to change it before execution. You can also use the up/down
arrow keys on your keyboard in the input box to move through the shell
history.

The SymPy Live shell is also available at http://live.sympy.org, with extra
features, like a mobile phone enhanced version and saved history.

This tutorial was the basis for a tutorial given at the 2013 SciPy conference
in Austin, TX. The website for that tutorial is here. It has links
to videos, materials, and IPython notebook exercises. The IPython notebook
exercises in particular are recommended to anyone going through this tutorial.

This tutorial aims to give an introduction to SymPy for someone who has not
used the library before. Many features of SymPy will be introduced in this
tutorial, but they will not be exhaustive. In fact, virtually every
functionality shown in this tutorial will have more options or capabilities
than what will be shown. The rest of the SymPy documentation serves as API
documentation, which extensively lists every feature and option of each
function.

These are the goals of this tutorial:

To give a guide, suitable for someone who has never used SymPy (but who has
used Python and knows the necessary mathematics).

To be written in a narrative format, which is both easy and fun to follow.
It should read like a book.

To give insightful examples and exercises, to help the reader learn and to
make it entertaining to work through.

To introduce concepts in a logical order.

To use good practices and idioms, and avoid antipatterns. Functions or
methodologies that tend to lead to antipatterns are avoided. Features that
are only useful to advanced users are not shown.

To be consistent. If there are multiple ways to do it, only the best way is
shown.

To avoid unnecessary duplication, it is assumed that previous sections of
the tutorial have already been read.

Feedback on this tutorial, or on SymPy in general is always welcome. Just
write to our mailing list.